| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 76 | | tagDensity | 0.184 | | leniency | 0.368 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2056 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 78.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2056 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "mosaic" | | 1 | "pulse" | | 2 | "flickered" | | 3 | "flicked" | | 4 | "pulsed" | | 5 | "etched" | | 6 | "shattered" | | 7 | "silence" | | 8 | "trembled" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 190 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 190 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 251 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2055 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 27.36% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 87 | | wordCount | 1590 | | uniqueNames | 12 | | maxNameDensity | 2.45 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 1 | | Quinn | 39 | | Sergeant | 1 | | Bell | 17 | | Kowalski | 1 | | Bloomsbury | 1 | | British | 1 | | Museum | 1 | | Eva | 20 | | Morris | 3 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Sergeant" | | 4 | "Bell" | | 5 | "Kowalski" | | 6 | "Museum" | | 7 | "Eva" | | 8 | "Morris" |
| | places | | | globalScore | 0.274 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 115 | | glossingSentenceCount | 1 | | matches | | 0 | "as though grasping for something beneath the tiles" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2055 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 251 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 150 | | mean | 13.7 | | std | 13.58 | | cv | 0.991 | | sampleLengths | | 0 | 10 | | 1 | 61 | | 2 | 22 | | 3 | 36 | | 4 | 8 | | 5 | 41 | | 6 | 6 | | 7 | 55 | | 8 | 13 | | 9 | 5 | | 10 | 5 | | 11 | 3 | | 12 | 26 | | 13 | 36 | | 14 | 4 | | 15 | 21 | | 16 | 1 | | 17 | 2 | | 18 | 10 | | 19 | 7 | | 20 | 4 | | 21 | 40 | | 22 | 7 | | 23 | 8 | | 24 | 5 | | 25 | 12 | | 26 | 7 | | 27 | 40 | | 28 | 4 | | 29 | 38 | | 30 | 25 | | 31 | 6 | | 32 | 10 | | 33 | 5 | | 34 | 1 | | 35 | 11 | | 36 | 4 | | 37 | 48 | | 38 | 2 | | 39 | 35 | | 40 | 24 | | 41 | 5 | | 42 | 4 | | 43 | 8 | | 44 | 16 | | 45 | 5 | | 46 | 16 | | 47 | 2 | | 48 | 23 | | 49 | 7 |
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| 86.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 10 | | totalSentences | 190 | | matches | | 0 | "been sealed" | | 1 | "been overturned" | | 2 | "was unbuttoned" | | 3 | "been found" | | 4 | "been dragged" | | 5 | "been pushed" | | 6 | "been placed" | | 7 | "was torn" | | 8 | "been opened" | | 9 | "was wrapped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 265 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 251 | | ratio | 0.008 | | matches | | 0 | "But the back of his head had not struck the tile; there was no swelling, no abrasion." | | 1 | "The blade had entered from the front—but there was no corresponding damage to the shirt beneath." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1594 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.026976160602258468 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.00439146800501882 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 251 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 251 | | mean | 8.19 | | std | 6.31 | | cv | 0.771 | | sampleLengths | | 0 | 10 | | 1 | 38 | | 2 | 13 | | 3 | 5 | | 4 | 5 | | 5 | 22 | | 6 | 10 | | 7 | 9 | | 8 | 17 | | 9 | 8 | | 10 | 17 | | 11 | 24 | | 12 | 6 | | 13 | 7 | | 14 | 26 | | 15 | 6 | | 16 | 16 | | 17 | 13 | | 18 | 5 | | 19 | 5 | | 20 | 3 | | 21 | 17 | | 22 | 9 | | 23 | 5 | | 24 | 31 | | 25 | 4 | | 26 | 21 | | 27 | 1 | | 28 | 2 | | 29 | 4 | | 30 | 6 | | 31 | 7 | | 32 | 4 | | 33 | 2 | | 34 | 38 | | 35 | 7 | | 36 | 8 | | 37 | 5 | | 38 | 6 | | 39 | 6 | | 40 | 7 | | 41 | 6 | | 42 | 34 | | 43 | 4 | | 44 | 11 | | 45 | 4 | | 46 | 11 | | 47 | 6 | | 48 | 6 | | 49 | 15 |
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| 47.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3147410358565737 | | totalSentences | 251 | | uniqueOpeners | 79 | |
| 40.40% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 165 | | matches | | 0 | "Instead, the dust had been" | | 1 | "Even the blood climbed in" |
| | ratio | 0.012 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 165 | | matches | | 0 | "Her boots struck the cracked" | | 1 | "She kept her left wrist" | | 2 | "He stood beside the body" | | 3 | "His throat had been cut." | | 4 | "It had risen." | | 5 | "She looked at him." | | 6 | "He moved closer to the" | | 7 | "His coat was unbuttoned." | | 8 | "She was short, freckled, and" | | 9 | "She had seen residue like" | | 10 | "She had kept the ash" | | 11 | "It had vanished from the" | | 12 | "His coat hem was dry" | | 13 | "He had been placed down" | | 14 | "She examined the chest wound" | | 15 | "He opened the folder and" | | 16 | "It was soot." | | 17 | "Its handle was wrapped in" | | 18 | "She had missed the tear." | | 19 | "Its fingers curled inward, one" |
| | ratio | 0.164 | |
| 44.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 137 | | totalSentences | 165 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn felt it" | | 2 | "The station had been sealed" | | 3 | "Quinn stepped over the chalk" | | 4 | "Her boots struck the cracked" | | 5 | "She kept her left wrist" | | 6 | "He stood beside the body" | | 7 | "Bell had been in uniform" | | 8 | "Quinn surveyed the platform before" | | 9 | "The abandoned station had become" | | 10 | "Stalls crowded the disused platform" | | 11 | "A torn sign reading CAMDEN" | | 12 | "His throat had been cut." | | 13 | "The blood had not spread." | | 14 | "It had risen." | | 15 | "A dark red ribbon hung" | | 16 | "Droplets hovered around it like" | | 17 | "Bell gestured to the body." | | 18 | "Quinn checked her watch." | | 19 | "She looked at him." |
| | ratio | 0.83 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 165 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 60 | | technicalSentenceCount | 6 | | matches | | 0 | "Detective Harlow Quinn felt it in the first gust that met her at the bottom of the service stairs: warm air pushing upward through the dark, carrying the smells…" | | 1 | "Yet blue flames burned in saucers along the platform, and the old tiled walls sweated as if the tunnels beyond were alive." | | 2 | "Stalls crowded the disused platform beneath ragged awnings: bottles of black liquid, cages lined with silver wire, bundles of dried herbs that twitched in their…" | | 3 | "The throat wound was ragged, but the skin surrounding it had browned as though cauterized." | | 4 | "Eva was watching Quinn with the wary concentration of someone who had already realized the detective was not going to accept the first explanation." | | 5 | "Her reflection stared back from the darkness, sharp jaw, cropped salt-and-pepper hair, brown eyes that had learned not to look away." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "Eva shouted (shout)" |
| | dialogueSentences | 76 | | tagDensity | 0.171 | | leniency | 0.342 | | rawRatio | 0.154 | | effectiveRatio | 0.053 | |